SLSU Faculty’s Cutting-Edge Research on Skin Rashes Classification Using Deep Learning Published in Lecture Notes in Networks and Systems

Southern Leyte State University (SLSU) proudly celebrates the remarkable achievement of its faculty members, Jannie Fleur V. Oraño, Francis Rey F. Padao, and Rhoderick D. Malangsa, whose groundbreaking research has been published in the esteemed Lecture Notes in Networks and Systems journal in 2023. Their innovative study, titled “A Deep Convolutional Neural Network for Skin Rashes Classification,” explores the use of advanced technology to enhance dermatological diagnosis.

The research delves into the potential of deep learning algorithms to classify skin rashes effectively, a critical task in the field of medical diagnostics. By employing a deep convolutional neural network (CNN), the team analyzed numerous images of skin conditions, paving the way for faster and more accurate diagnoses. This innovative approach not only demonstrates the power of artificial intelligence in healthcare but also highlights the role of technology in improving patient outcomes.

With their study involving extensive data analysis, Oraño, Padao, and Malangsa have created a framework that could revolutionize how medical professionals approach skin rashes. The application of CNNs enables more nuanced understanding and identification of skin conditions, ultimately leading to better treatment strategies and patient care.

This research aligns with Sustainable Development Goal 3 (Good Health and Well-Being), as it seeks to enhance healthcare accessibility and effectiveness through the integration of technology. The implications of this work are significant, offering a glimpse into the future of medical diagnostics, where AI-driven solutions could play a vital role in improving healthcare services.

SLSU remains committed to fostering an environment of innovation and academic excellence. The university looks forward to supporting more pioneering studies that will contribute to advancements in both local and global health sectors, reinforcing its dedication to societal betterment.

How to cite: Oraño, J. F. V., Padao, F. R. F., & Malangsa, R. D. (2023). A deep convolutional neural network for skin rashes classification. Lecture Notes in Networks and Systems, 556, 339–348.
To read full content:
https://www.scopus.com/record/display.uri?eid=2-s2.0-85140452421&doi=10.1007%2f978-3-031-17601-2_33&origin=inward&txGid=ddc7d7eac8bb8694c99e7aa4a1a6efd4
https://doi.org/10.1007/978-3-031-17601-2_33